Integrative Bioinformatic Analyses of Global Transcriptome Data Decipher Novel Molecular Insights into Cardiac Anti-Fibrotic Therapies.
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Authors
Fuchs, MaximilianKreutzer, Fabian Philipp
Kapsner, Lorenz A
Mitzka, Saskia
Just, Annette
Perbellini, Filippo
Terracciano, Cesare M
Xiao, Ke
Geffers, Robert
Bogdan, Christian
Prokosch, Hans-Ulrich
Fiedler, Jan
Thum, Thomas
Kunz, Meik
Issue Date
2020-07-02
Metadata
Show full item recordAbstract
Integrative bioinformatics is an emerging field in the big data era, offering a steadily increasing number of algorithms and analysis tools. However, for researchers in experimental life sciences it is often difficult to follow and properly apply the bioinformatical methods in order to unravel the complexity and systemic effects of omics data. Here, we present an integrative bioinformatics pipeline to decipher crucial biological insights from global transcriptome profiling data to validate innovative therapeutics. It is available as a web application for an interactive and simplified analysis without the need for programming skills or deep bioinformatics background. The approach was applied to an ex vivo cardiac model treated with natural anti-fibrotic compounds and we obtained new mechanistic insights into their anti-fibrotic action and molecular interplay with miRNAs in cardiac fibrosis. Several gene pathways associated with proliferation, extracellular matrix processes and wound healing were altered, and we could identify micro (mi) RNA-21-5p and miRNA-223-3p as key molecular components related to the anti-fibrotic treatment. Importantly, our pipeline is not restricted to a specific cell type or disease and can be broadly applied to better understand the unprecedented level of complexity in big data research.Citation
Int J Mol Sci. 2020;21(13):4727. Published 2020 Jul 2. doi:10.3390/ijms21134727.Affiliation
HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.Publisher
MDPIPubMed ID
32630753Type
ArticleLanguage
enEISSN
1422-0067ae974a485f413a2113503eed53cd6c53
10.3390/ijms21134727
Scopus Count
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- Creative Commons
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International
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